论文检索

完全区组分析中渐近分布无关方法的比较AI 解读

The Friedman test (or sign test when k = 2) depends entirely on within-block rankings. In a recent paper, Quade (1979) attempted to provide a test with more power than the Friedman test by considering a k-sample extension of the Wilcoxon signed ranks test. This is done by taking advantage of the between-block information. A third way to approach the problem and still retain both the within- and between-block information is first to transform all the observations to ranks…

秩与秩得分变换数据下双向设计的 F 统计量AI 解读

The limiting null distribution of the usual F statistic for main effects in the two-way layout is shown to have the same limiting distribution when applied to ranks and scores based on ranks as when applied to normal data. The limit is taken as the cell size N increases without bound. The denominator of the F statistic times (J − 1)/J is shown to provide an unbiased and consistent estimator of the limit (as N → ∞) of N -1 times the variance of the treatment sum of scores…

双指数分布族中非参数位置检验的小样本功效AI 解读

Eight nonparametric tests are examined in a small-sample setting. Their power functions are compared with the locally most powerful (LMP) linear rank test, primarily to see over which range the LMP test retains good power. All tests are two-sample tests, the populations are governed by the double exponential distribution, and the sample sizes are m = 5, n = 5, and m = 5, n = 4. The LMP test performs uniformly well, even under nonlocal alternatives, while its asymptotically…

双指数分布族中非参数位置检验的小样本功效AI 解读

Eight nonparametric tests are examined in a small-sample setting. Their power functions are compared with the locally most powerful (LMP) linear rank test, primarily to see over which range the LMP test retains good power. All tests are two-sample tests, the populations are governed by the double exponential distribution, and the sample sizes are m = 5, n = 5, and m = 5, n = 4. The LMP test performs uniformly well, even under nonlocal alternatives, while its asymptotically…

不要求分布函数连续的单样本、双样本与多样本秩检验AI 解读

The theory of rank tests has been developed primarily for continuous random variables. Recently the asymptotic theory of linear rank tests has been extended to include purely discrete random variables under the null hypothesis of randomness (including the two-sample and $k$-sample problems) and under contiguous alternatives, for the two methods of assigning scores known as the average scores method and the randomized ranks method. In this paper the theory of rank tests is…

不连续分布的 Kolmogorov 拟合优度检验AI 解读

The Kolmogorov goodness-of-fit test is known to be conservative when the hypothesized distribution function is not continuous. A method for finding the exact critical level (approximate in the two-sided case) and the power in such cases is derived. Thus the Kolmogorov test may be used as an exact goodness-of-fit test for all completely specified distribution functions, whether continuous or not continuous. Several examples of the application of this extension of the…

摘要暂缺

Two nonparametric tests are presented for analyzing data from a one-way layout. Their principal characteristic is ease in computation. One test is intended for k samples of equal size n, and the other is for k samples of possibly unequal sample sizes. Both tests may be regarded as generalizations of Mosteller's slippage test. Multiple decision aspects of both tests are discussed. Monte Carlo studies show the first test to be more powerful than the F test in some situations,…